Antiviral NK cell responses in HIV infection: II. viral strategies for evasion and lessons for immunotherapy and vaccination
Bibliographic record
Abstract
As is the case in other viral infections, humans respond to HIV infection by activating their NK cells. However, the virus uses several strategies to neutralize and evade the host's NK cell responses. Consequently, it is not surprising that NK cell functions become compromised in HIV-infected individuals in early stages of the infection. The compromised NK cell functions also adversely affect several aspects of the host's antiviral adaptive immune responses. Researchers have made significant progress in understanding how HIV counters NK cell responses of the host. This knowledge has opened new avenues for immunotherapy and vaccination against this infection. In the first part of this review article, we gave an overview of our current knowledge of NK cell biology and discussed how the genes encoding NK cell receptors and their ligands determine innate genetic resistance/susceptibilty of humans against HIV infections and AIDS. In this second part, we discuss NK cell responses, viral strategies to counter these responses, and finally, their implications for anti-HIV immunotherapy and vaccination.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".